Wind and Structures

  • 제12권6호
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  • Pages.519-540
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  • 2009
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  • 1226-6116(pISSN)
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  • 1598-6225(eISSN)
테크노프레스 (Techno-Press)
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Experimental and numerical identification of flutter derivatives for nine bridge deck sections

  • 투고 : 2009.02.25
  • 심사 : 2009.07.16
  • 발행 : 2009.11.25
⟨ 이전 논문 다음 논문 ⟩

초록

This paper presents the results of a study into experimental and numerical methods for the identification of bridge deck flutter derivatives. Nine bridge deck sections were investigated in a water tunnel in order to create an empirical reference set for numerical investigations. The same sections, plus a wide range of further sections, were studied numerically using a commercially available CFD code. The experimental and numerical results were compared with respect to accuracy, sensitivity, and practical suitability. Furthermore, the relevance of the effective angle of attack, the possible assessment of non-critical vibrations, and the formulation of lateral vibrations were studied. Selected results are presented in this paper. The full set of raw data is available online to provide researchers and engineers with a comprehensive benchmarking tool.

키워드

참고문헌

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피인용 문헌

  1. LMI-based gain scheduling for bridge flutter control using eccentric rotational actuators vol.33, pp.4, 2012, https://doi.org/10.1002/oca.1010
  2. Bridge deck flutter derivatives: Efficient numerical evaluation exploiting their interdependence vol.136, 2015, https://doi.org/10.1016/j.jweia.2014.11.006
  3. Flutter characteristics of twin-box girder bridges with vertical central stabilizers vol.133, 2017, https://doi.org/10.1016/j.engstruct.2016.12.009
  4. Transfer function approximation of motion-induced aerodynamic forces with rational functions vol.14, pp.2, 2011, https://doi.org/10.12989/was.2011.14.2.133
  5. Numerical simulation of feedback flutter control for a single-box-girder suspension bridge by twin-winglet system vol.169, 2017, https://doi.org/10.1016/j.jweia.2017.07.013
  6. Identification of flutter derivatives of bridge decks using CFD-based discrete-time aerodynamic models vol.18, pp.3, 2014, https://doi.org/10.12989/was.2014.18.3.215
  7. Aeroelastic control of long-span suspension bridges with controllable winglets vol.23, pp.12, 2016, https://doi.org/10.1002/stc.1839
  8. Methods for flutter stability analysis of long-span bridges: a review vol.170, pp.4, 2017, https://doi.org/10.1680/jbren.15.00039
  9. On the identification of flutter derivatives of bridge decks via RANS turbulence models: Benchmarking on rectangular prisms vol.76, pp.None, 2014, https://doi.org/10.1016/j.engstruct.2014.07.027
  10. Examination of experimental errors in Scanlan derivatives of a closed-box bridge deck vol.26, pp.4, 2009, https://doi.org/10.12989/was.2018.26.4.231
  11. Artificial Neural Network model to predict the flutter velocity of suspension bridges vol.233, pp.None, 2020, https://doi.org/10.1016/j.compstruc.2020.106236